Principal Component Analysis Detailed Explanation
Principal Component Analysis (PCA) is a powerful statistical technique for dimensionality reduction and data visualization. PCA allows us to transform high-dimensional data into a lower-dimensional space while retaining most of the original variance in the data. This makes it easier to visualize, analyze and model complex datasets. ... Read More
Naïve Bayes Algorithm Detailed Explanation
The naïve Bayes algorithm is a popular machine learning algorithm used for text-based tasks. Naïve Bayes is a probabilistic classifier that returns the probability of a test point belonging to a class rather than the label of the test point. To learn in detail about the algorithm refer to the post. ... Read More
Explaining ML model results using Cumulative gains and lift instead of ROC curve are much more intuitive
As Data Scientists, our day-to-day challenge is to break down technical jargon so that businesses can understand the results of the machine learning model. One simple way to explain the results of the classification prediction model is using cumulative and lift curves. In this post, we have covered the magical calculation that can help you to explain the business results of the ML model. ... Read More
Angular CLI Cheat Sheet
T he Angular team has brought in a really handy tool to bootstrap the Angular application and also to add a new feature to the app. The tool is known as angular-cli. To install angular-cli to the system we need to install nodeJS. Once we have installed it we need to install npm dependency angular-cli globally. Once installed, open the terminal/ command prompt and run a command: ... Read More
Using an expected value for the designed Machine Learning solutions
Expected value can help you effectively sell your designed machine learning solutions to businesses. It summarizes the results from the developed machine learning model and gives a way to explain results to businesses effectively. Want to know how? ... Read More
Support Vector Machines Detailed Explanation
There are a lot of algorithms like logistic regression, Naive Bayes, etc that are used to solve classification problems. Though these algorithms are popular and used across the industry, they fail to classify complex classification tasks like image classification, voice detection, etc. Support Vector Machines are also known as SVM which are capable of dealing with quite complex problems, where models like logistic regression mostly fail. A few of the properties and use cases of the SVM algorithm are: ... Read More
Confound between Covariance and Correlation? Me too.
How covariance and correlation are different from one another? What is causation and is it different? In this article, I have explained differences and have also covered different types of correlations such as Pearson correlation Kendall rank correlation, Spearman correlation, and Point-Biserial correlation. ... Read More
SQLAlchemy - ORM for Python
The post explains about the SQLAlchemy package which is used for connecting to the Object -Relational databases (SQLite, Postgres, MySql etc). Here we will be discussing about how to connect to the database using SQLAlchemy package and create database, create tables in database, Inserting data in the tables, various ways to select data from the table, Delete operations, update operations and lot more. This post assumes that reader has basic knowledge about SQL. ... Read More
